You are given the daily sales of a Walmart store from May 26 to June 29 in the

dataset below. Forecast the daily sales from June 30 to July 6.

Make sure your forecasts include any adjustments for trend and seasonality.

• Draw a line chart of your data.
• What do the seasonality indexes tell you?
• What are the forecasted sales amounts from June 30 to July 6.

Average Sales from 5/26 to 6/29 (in millions) \begin{tabular}{|l|l|r|} \hline Date & Day & Visitors \\ \hline 26-May & Mon & 706 \\ \hline 27-May & Tue & 904 \\ \hline 28-May & Wed & 892 \\ \hline 29-May & Thu & 1,215 \\ \hline 30-May & Fri & 1,685 \\ \hline 31-May & Sat & 2,478 \\ \hline 1-Jun & Sun & 3,197 \\ \hline 2-Jun & Mon & 985 \\ \hline 3-Jun & Tue & 837 \\ \hline 4-Jun & Wed & 1,555 \\ \hline 5-Jun & Thu & 1,570 \\ \hline 6-Jun & Fri & 2,401 \\ \hline 7-Jun & Sat & 4,273 \\ \hline 8-Jun & Sun & 3,303 \\ \hline 9-Jun & Mon & 1,612 \\ \hline 10-Jun & Tue & 1,484 \\ \hline 11-Jun & Wed & 2,603 \\ \hline 12-Jun & Thu & 2,484 \\ \hline 13-Jun & Fri & 2,906 \\ \hline 14-Jun & Sat & 5,212 \\ \hline 15-Jun & Sun & 4,561 \\ \hline 16-Jun & Mon & 1,948 \\ \hline 17-Jun & Tue & 2,177 \\ \hline 18-Jun & Wed & 2,753 \\ \hline 19-Jun & Thu & 3,019 \\ \hline 20-Jun & Fri & 3,402 \\ \hline 21-Jun & Sat & 6,081 \\ \hline 22-Jun & Sun & 5,414 \\ \hline 23-Jun & Mon & 2,676 \\ \hline 24-Jun & Tue & 2,681 \\ \hline 25-Jun & Wed & 2,904 \\ \hline 26-Jun & Thu & 2,510 \\ \hline 27-Jun & Fri & 4,512 \\ \hline 28-Jun & Sat & 6,512 \\ \hline 29-Jun & Sun & 7,834 \\ \hline \end{tabular}